Overview

Dataset statistics

Number of variables44
Number of observations40336
Missing cells509176
Missing cells (%)28.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.5 MiB
Average record size in memory352.0 B

Variable types

Numeric40
Categorical4

Alerts

SBP is highly correlated with MAPHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with MAPHigh correlation
BaseExcess is highly correlated with HCO3 and 1 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 1 other fieldsHigh correlation
pH is highly correlated with BaseExcessHigh correlation
PaCO2 is highly correlated with HCO3High correlation
AST is highly correlated with Bilirubin_directHigh correlation
BUN is highly correlated with CreatinineHigh correlation
Creatinine is highly correlated with BUNHigh correlation
Bilirubin_direct is highly correlated with AST and 1 other fieldsHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with HoursHigh correlation
SepsisLabel is highly correlated with SepsisHigh correlation
Sepsis is highly correlated with SepsisLabelHigh correlation
Hours is highly correlated with ICULOSHigh correlation
SBP is highly correlated with MAP and 1 other fieldsHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with SBP and 1 other fieldsHigh correlation
BaseExcess is highly correlated with HCO3 and 1 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 1 other fieldsHigh correlation
pH is highly correlated with BaseExcessHigh correlation
PaCO2 is highly correlated with HCO3High correlation
BUN is highly correlated with Creatinine and 1 other fieldsHigh correlation
Creatinine is highly correlated with BUN and 1 other fieldsHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Phosphate is highly correlated with BUN and 1 other fieldsHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with HoursHigh correlation
SepsisLabel is highly correlated with SepsisHigh correlation
Sepsis is highly correlated with SepsisLabelHigh correlation
Hours is highly correlated with ICULOSHigh correlation
SBP is highly correlated with MAPHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with MAPHigh correlation
BaseExcess is highly correlated with HCO3High correlation
HCO3 is highly correlated with BaseExcessHigh correlation
BUN is highly correlated with CreatinineHigh correlation
Creatinine is highly correlated with BUNHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with HoursHigh correlation
SepsisLabel is highly correlated with SepsisHigh correlation
Sepsis is highly correlated with SepsisLabelHigh correlation
Hours is highly correlated with ICULOSHigh correlation
Unit2 is highly correlated with Unit1High correlation
Unit1 is highly correlated with Unit2High correlation
DBP has 7411 (18.4%) missing values Missing
EtCO2 has 37120 (92.0%) missing values Missing
BaseExcess has 27126 (67.3%) missing values Missing
HCO3 has 20119 (49.9%) missing values Missing
FiO2 has 22527 (55.8%) missing values Missing
pH has 21401 (53.1%) missing values Missing
PaCO2 has 21980 (54.5%) missing values Missing
SaO2 has 27248 (67.6%) missing values Missing
AST has 25979 (64.4%) missing values Missing
BUN has 2018 (5.0%) missing values Missing
Alkalinephos has 26163 (64.9%) missing values Missing
Calcium has 5339 (13.2%) missing values Missing
Chloride has 18925 (46.9%) missing values Missing
Creatinine has 2049 (5.1%) missing values Missing
Bilirubin_direct has 38279 (94.9%) missing values Missing
Glucose has 1580 (3.9%) missing values Missing
Lactate has 27843 (69.0%) missing values Missing
Magnesium has 4931 (12.2%) missing values Missing
Phosphate has 12015 (29.8%) missing values Missing
Potassium has 1867 (4.6%) missing values Missing
Bilirubin_total has 26088 (64.7%) missing values Missing
TroponinI has 33283 (82.5%) missing values Missing
Hct has 2317 (5.7%) missing values Missing
Hgb has 2448 (6.1%) missing values Missing
PTT has 20098 (49.8%) missing values Missing
WBC has 2625 (6.5%) missing values Missing
Fibrinogen has 35821 (88.8%) missing values Missing
Platelets has 2577 (6.4%) missing values Missing
Unit1 has 15617 (38.7%) missing values Missing
Unit2 has 15617 (38.7%) missing values Missing
FiO2 is highly skewed (γ1 = 133.2689459) Skewed
PatientID has unique values Unique
BaseExcess has 1020 (2.5%) zeros Zeros
HospAdmTime has 1313 (3.3%) zeros Zeros
SepsisLabel has 37404 (92.7%) zeros Zeros

Reproduction

Analysis started2021-11-29 10:25:19.789930
Analysis finished2021-11-29 10:25:37.670427
Duration17.88 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

PatientID
Real number (ℝ≥0)

UNIQUE

Distinct40336
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59671.27286
Minimum1
Maximum120000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:37.715921image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2017.75
Q110084.75
median20475.5
Q3109916.25
95-th percentile117983.25
Maximum120000
Range119999
Interquartile range (IQR)99831.5

Descriptive statistics

Standard deviation50251.33712
Coefficient of variation (CV)0.842136169
Kurtosis-1.946653503
Mean59671.27286
Median Absolute Deviation (MAD)20307
Skewness0.01560297418
Sum2406900462
Variance2525196883
MonotonicityStrictly increasing
2021-11-29T11:25:37.821125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11
 
< 0.1%
1065591
 
< 0.1%
1065521
 
< 0.1%
1065531
 
< 0.1%
1065541
 
< 0.1%
1065551
 
< 0.1%
1065561
 
< 0.1%
1065571
 
< 0.1%
1065581
 
< 0.1%
1065601
 
< 0.1%
Other values (40326)40326
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
61
< 0.1%
71
< 0.1%
81
< 0.1%
91
< 0.1%
101
< 0.1%
ValueCountFrequency (%)
1200001
< 0.1%
1199991
< 0.1%
1199981
< 0.1%
1199971
< 0.1%
1199961
< 0.1%
1199951
< 0.1%
1199941
< 0.1%
1199931
< 0.1%
1199921
< 0.1%
1199911
< 0.1%

HR
Real number (ℝ≥0)

Distinct26769
Distinct (%)66.4%
Missing5
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean83.8051147
Minimum30.25806452
Maximum174.6976744
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:37.924228image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30.25806452
5-th percentile61.21040373
Q173.46666667
median83.0952381
Q393.17416582
95-th percentile109.0399225
Maximum174.6976744
Range144.4396099
Interquartile range (IQR)19.70749916

Descriptive statistics

Standard deviation14.63198906
Coefficient of variation (CV)0.1745954183
Kurtosis0.2061531987
Mean83.8051147
Median Absolute Deviation (MAD)9.845238095
Skewness0.3337958374
Sum3379944.081
Variance214.0951038
MonotonicityNot monotonic
2021-11-29T11:25:38.022083image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8041
 
0.1%
7037
 
0.1%
6836
 
0.1%
8136
 
0.1%
9035
 
0.1%
8335
 
0.1%
7735
 
0.1%
8835
 
0.1%
8634
 
0.1%
7632
 
0.1%
Other values (26759)39975
99.1%
ValueCountFrequency (%)
30.258064521
< 0.1%
33.361
< 0.1%
35.410256411
< 0.1%
37.285714291
< 0.1%
37.960526321
< 0.1%
38.783783781
< 0.1%
38.9843751
< 0.1%
39.619047621
< 0.1%
39.867647061
< 0.1%
40.03260871
< 0.1%
ValueCountFrequency (%)
174.69767441
< 0.1%
158.21428571
< 0.1%
156.14285711
< 0.1%
1531
< 0.1%
150.88888891
< 0.1%
150.16666671
< 0.1%
148.51960781
< 0.1%
145.81
< 0.1%
145.65454551
< 0.1%
145.25862071
< 0.1%

O2Sat
Real number (ℝ≥0)

Distinct10662
Distinct (%)26.4%
Missing18
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean97.15382246
Minimum27
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:38.127539image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile94.14255533
Q196.14516129
median97.39130435
Q398.5
95-th percentile99.65482348
Maximum100
Range73
Interquartile range (IQR)2.35483871

Descriptive statistics

Standard deviation2.095485598
Coefficient of variation (CV)0.02156874063
Kurtosis98.08574629
Mean97.15382246
Median Absolute Deviation (MAD)1.168695652
Skewness-5.421248166
Sum3917047.814
Variance4.391059891
MonotonicityNot monotonic
2021-11-29T11:25:38.225960image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100349
 
0.9%
97263
 
0.7%
98242
 
0.6%
97.5205
 
0.5%
99204
 
0.5%
98.5198
 
0.5%
96190
 
0.5%
96.5165
 
0.4%
99.5128
 
0.3%
95113
 
0.3%
Other values (10652)38261
94.9%
ValueCountFrequency (%)
271
< 0.1%
34.251
< 0.1%
491
< 0.1%
55.51
< 0.1%
56.302631581
< 0.1%
57.51
< 0.1%
61.954545451
< 0.1%
65.51
< 0.1%
65.81
< 0.1%
66.251
< 0.1%
ValueCountFrequency (%)
100349
0.9%
99.990740741
 
< 0.1%
99.98936171
 
< 0.1%
99.988888891
 
< 0.1%
99.986842111
 
< 0.1%
99.986111112
 
< 0.1%
99.985714291
 
< 0.1%
99.985294121
 
< 0.1%
99.9843751
 
< 0.1%
99.983870972
 
< 0.1%

Temp
Real number (ℝ≥0)

Distinct14175
Distinct (%)35.4%
Missing284
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean36.84286622
Minimum30.5
Maximum39.7375
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:38.331732image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum30.5
5-th percentile36.02833333
Q136.5
median36.81240385
Q337.18272727
95-th percentile37.75285714
Maximum39.7375
Range9.2375
Interquartile range (IQR)0.6827272727

Descriptive statistics

Standard deviation0.5481941617
Coefficient of variation (CV)0.01487924849
Kurtosis3.03984375
Mean36.84286622
Median Absolute Deviation (MAD)0.3424038462
Skewness-0.1382893026
Sum1475630.478
Variance0.3005168389
MonotonicityNot monotonic
2021-11-29T11:25:38.429978image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.5297
 
0.7%
36.6252
 
0.6%
36.4200
 
0.5%
36.9177
 
0.4%
37177
 
0.4%
36.7173
 
0.4%
36.8165
 
0.4%
36.75146
 
0.4%
36.3140
 
0.3%
36135
 
0.3%
Other values (14165)38190
94.7%
(Missing)284
 
0.7%
ValueCountFrequency (%)
30.51
< 0.1%
31.444444441
< 0.1%
32.307142861
< 0.1%
32.351
< 0.1%
32.442857141
< 0.1%
32.456363641
< 0.1%
32.521
< 0.1%
32.751
< 0.1%
32.81
< 0.1%
32.932352941
< 0.1%
ValueCountFrequency (%)
39.73751
< 0.1%
39.714516131
< 0.1%
39.6751
< 0.1%
39.611
< 0.1%
39.507142861
< 0.1%
39.3851
< 0.1%
39.366666671
< 0.1%
39.3581
< 0.1%
39.34751
< 0.1%
39.222916671
< 0.1%

SBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct27948
Distinct (%)69.8%
Missing282
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean123.3214349
Minimum35
Maximum214.8181818
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:38.529828image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile97.96666667
Q1110.375
median121.3007353
Q3134.6421429
95-th percentile155.5475419
Maximum214.8181818
Range179.8181818
Interquartile range (IQR)24.26714286

Descriptive statistics

Standard deviation17.83022648
Coefficient of variation (CV)0.1445833524
Kurtosis0.2270386824
Mean123.3214349
Median Absolute Deviation (MAD)11.94352159
Skewness0.4720636653
Sum4939516.753
Variance317.9169762
MonotonicityNot monotonic
2021-11-29T11:25:38.627271image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12534
 
0.1%
11633
 
0.1%
12833
 
0.1%
109.529
 
0.1%
11728
 
0.1%
12128
 
0.1%
11328
 
0.1%
12728
 
0.1%
11427
 
0.1%
11027
 
0.1%
Other values (27938)39759
98.6%
(Missing)282
 
0.7%
ValueCountFrequency (%)
351
< 0.1%
48.517241381
< 0.1%
52.2751
< 0.1%
54.541666671
< 0.1%
56.298076921
< 0.1%
57.31251
< 0.1%
57.392857141
< 0.1%
57.5751
< 0.1%
58.166666671
< 0.1%
58.7251
< 0.1%
ValueCountFrequency (%)
214.81818181
< 0.1%
207.05555561
< 0.1%
203.7751
< 0.1%
200.78301891
< 0.1%
200.15555561
< 0.1%
197.79166671
< 0.1%
197.21
< 0.1%
197.14285711
< 0.1%
196.80434781
< 0.1%
194.66666671
< 0.1%

MAP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct29015
Distinct (%)72.1%
Missing104
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean82.56308065
Minimum22
Maximum149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:38.729818image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile65.28125
Q173.58333333
median80.81818182
Q390
95-th percentile105.817791
Maximum149
Range127
Interquartile range (IQR)16.41666667

Descriptive statistics

Standard deviation12.57989961
Coefficient of variation (CV)0.1523671296
Kurtosis0.6877957276
Mean82.56308065
Median Absolute Deviation (MAD)8.043806818
Skewness0.6909986699
Sum3321677.861
Variance158.2538742
MonotonicityNot monotonic
2021-11-29T11:25:38.922305image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8542
 
0.1%
8041
 
0.1%
79.538
 
0.1%
7938
 
0.1%
8236
 
0.1%
7635
 
0.1%
8134
 
0.1%
9232
 
0.1%
8732
 
0.1%
7831
 
0.1%
Other values (29005)39873
98.9%
(Missing)104
 
0.3%
ValueCountFrequency (%)
221
< 0.1%
32.425185191
< 0.1%
34.291666671
< 0.1%
36.19151
< 0.1%
38.468751
< 0.1%
40.634193551
< 0.1%
411
< 0.1%
41.81
< 0.1%
41.9171
< 0.1%
43.0421
< 0.1%
ValueCountFrequency (%)
1491
< 0.1%
143.22857141
< 0.1%
141.54166671
< 0.1%
141.06451611
< 0.1%
140.72413791
< 0.1%
140.40566041
< 0.1%
140.06578951
< 0.1%
1401
< 0.1%
139.93751
< 0.1%
138.99074071
< 0.1%

DBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct20708
Distinct (%)62.9%
Missing7411
Missing (%)18.4%
Infinite0
Infinite (%)0.0%
Mean64.09587619
Minimum24
Maximum135.7222222
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:39.029345image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile48.25
Q156.43396226
median62.91666667
Q370.65909091
95-th percentile83.72857143
Maximum135.7222222
Range111.7222222
Interquartile range (IQR)14.22512864

Descriptive statistics

Standard deviation10.93405346
Coefficient of variation (CV)0.1705890317
Kurtosis0.6409361117
Mean64.09587619
Median Absolute Deviation (MAD)6.995614035
Skewness0.5638127481
Sum2110356.723
Variance119.553525
MonotonicityNot monotonic
2021-11-29T11:25:39.129524image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6150
 
0.1%
6945
 
0.1%
6245
 
0.1%
6044
 
0.1%
6742
 
0.1%
5542
 
0.1%
67.541
 
0.1%
7041
 
0.1%
6540
 
0.1%
5940
 
0.1%
Other values (20698)32495
80.6%
(Missing)7411
 
18.4%
ValueCountFrequency (%)
241
 
< 0.1%
27.333333331
 
< 0.1%
27.5251
 
< 0.1%
28.583333332
< 0.1%
293
< 0.1%
29.095744681
 
< 0.1%
29.5751
 
< 0.1%
30.414285711
 
< 0.1%
30.764705881
 
< 0.1%
31.022222221
 
< 0.1%
ValueCountFrequency (%)
135.72222221
< 0.1%
1341
< 0.1%
116.54545451
< 0.1%
116.18918921
< 0.1%
116.01351351
< 0.1%
115.83333331
< 0.1%
115.13636361
< 0.1%
114.8751
< 0.1%
113.28571431
< 0.1%
112.26923081
< 0.1%

Resp
Real number (ℝ≥0)

Distinct15947
Distinct (%)39.6%
Missing71
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean18.53796649
Minimum1
Maximum56.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:39.231773image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.85263952
Q116.38095238
median18.14285714
Q320.27941176
95-th percentile24.54324786
Maximum56.25
Range55.25
Interquartile range (IQR)3.898459384

Descriptive statistics

Standard deviation3.40576537
Coefficient of variation (CV)0.1837183906
Kurtosis3.563885383
Mean18.53796649
Median Absolute Deviation (MAD)1.928571429
Skewness0.8367202864
Sum746431.2208
Variance11.59923775
MonotonicityNot monotonic
2021-11-29T11:25:39.326462image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18360
 
0.9%
16211
 
0.5%
17200
 
0.5%
17.5167
 
0.4%
19136
 
0.3%
18.5125
 
0.3%
16.5123
 
0.3%
20108
 
0.3%
17.3333333392
 
0.2%
1592
 
0.2%
Other values (15937)38651
95.8%
ValueCountFrequency (%)
14
< 0.1%
1.3333333332
< 0.1%
1.52
< 0.1%
1.5833333331
 
< 0.1%
1.6363636361
 
< 0.1%
1.6428571431
 
< 0.1%
1.7647058821
 
< 0.1%
1.8333333331
 
< 0.1%
1.8421052631
 
< 0.1%
1.91
 
< 0.1%
ValueCountFrequency (%)
56.251
< 0.1%
561
< 0.1%
50.041666671
< 0.1%
44.285714291
< 0.1%
41.666666671
< 0.1%
40.222222221
< 0.1%
40.214285711
< 0.1%
39.52
< 0.1%
38.916666671
< 0.1%
38.153846151
< 0.1%

EtCO2
Real number (ℝ≥0)

MISSING

Distinct1928
Distinct (%)60.0%
Missing37120
Missing (%)92.0%
Infinite0
Infinite (%)0.0%
Mean33.09096109
Minimum10
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:39.429566image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile17.8875
Q128.34903846
median33.05
Q337.25
95-th percentile43.25347222
Maximum100
Range90
Interquartile range (IQR)8.900961538

Descriptive statistics

Standard deviation10.19338005
Coefficient of variation (CV)0.3080412207
Kurtosis16.96107567
Mean33.09096109
Median Absolute Deviation (MAD)4.45
Skewness2.739708572
Sum106420.5309
Variance103.9049968
MonotonicityNot monotonic
2021-11-29T11:25:39.527222image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3528
 
0.1%
3426
 
0.1%
4023
 
0.1%
3322
 
0.1%
3621
 
0.1%
3920
 
< 0.1%
3219
 
< 0.1%
2819
 
< 0.1%
3719
 
< 0.1%
34.518
 
< 0.1%
Other values (1918)3001
 
7.4%
(Missing)37120
92.0%
ValueCountFrequency (%)
104
< 0.1%
10.1251
 
< 0.1%
10.55
< 0.1%
10.833333331
 
< 0.1%
116
< 0.1%
11.151
 
< 0.1%
11.251
 
< 0.1%
11.51
 
< 0.1%
11.751
 
< 0.1%
11.846153851
 
< 0.1%
ValueCountFrequency (%)
1007
< 0.1%
994
< 0.1%
98.51
 
< 0.1%
986
< 0.1%
97.51
 
< 0.1%
97.251
 
< 0.1%
977
< 0.1%
962
 
< 0.1%
951
 
< 0.1%
942
 
< 0.1%

BaseExcess
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct2037
Distinct (%)15.4%
Missing27126
Missing (%)67.3%
Infinite0
Infinite (%)0.0%
Mean-0.4712249706
Minimum-25
Maximum25
Zeros1020
Zeros (%)2.5%
Negative7070
Negative (%)17.5%
Memory size315.2 KiB
2021-11-29T11:25:39.627100image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-25
5-th percentile-6.423214286
Q1-2.205882353
median-0.3333333333
Q31.097727273
95-th percentile5.666666667
Maximum25
Range50
Interquartile range (IQR)3.303609626

Descriptive statistics

Standard deviation3.850798288
Coefficient of variation (CV)-8.171889285
Kurtosis4.752679783
Mean-0.4712249706
Median Absolute Deviation (MAD)1.666666667
Skewness-0.07405872077
Sum-6224.881862
Variance14.82864746
MonotonicityNot monotonic
2021-11-29T11:25:39.723269image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01020
 
2.5%
-1489
 
1.2%
1465
 
1.2%
-2371
 
0.9%
2325
 
0.8%
3252
 
0.6%
-3241
 
0.6%
-0.5220
 
0.5%
0.5215
 
0.5%
4175
 
0.4%
Other values (2027)9437
 
23.4%
(Missing)27126
67.3%
ValueCountFrequency (%)
-251
< 0.1%
-24.51
< 0.1%
-242
< 0.1%
-22.666666671
< 0.1%
-22.366666671
< 0.1%
-22.251
< 0.1%
-21.751
< 0.1%
-21.61
< 0.1%
-21.071428571
< 0.1%
-20.52
< 0.1%
ValueCountFrequency (%)
251
 
< 0.1%
241
 
< 0.1%
212
< 0.1%
20.714285711
 
< 0.1%
201
 
< 0.1%
19.333333331
 
< 0.1%
193
< 0.1%
18.818181821
 
< 0.1%
18.81
 
< 0.1%
183
< 0.1%

HCO3
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1003
Distinct (%)5.0%
Missing20119
Missing (%)49.9%
Infinite0
Infinite (%)0.0%
Mean24.38459267
Minimum5
Maximum54.33333333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:39.817718image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile18
Q122.2
median24.33333333
Q326.5
95-th percentile30.5
Maximum54.33333333
Range49.33333333
Interquartile range (IQR)4.3

Descriptive statistics

Standard deviation3.887861096
Coefficient of variation (CV)0.1594392471
Kurtosis3.098860851
Mean24.38459267
Median Absolute Deviation (MAD)2.166666667
Skewness0.4054029494
Sum492983.31
Variance15.1154639
MonotonicityNot monotonic
2021-11-29T11:25:39.915099image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
251369
 
3.4%
241342
 
3.3%
261165
 
2.9%
231155
 
2.9%
22895
 
2.2%
27873
 
2.2%
28577
 
1.4%
21566
 
1.4%
24.5536
 
1.3%
23.5466
 
1.2%
Other values (993)11273
27.9%
(Missing)20119
49.9%
ValueCountFrequency (%)
51
 
< 0.1%
61
 
< 0.1%
6.52
 
< 0.1%
71
 
< 0.1%
7.21
 
< 0.1%
7.4285714291
 
< 0.1%
7.71
 
< 0.1%
85
< 0.1%
8.3636363641
 
< 0.1%
8.51
 
< 0.1%
ValueCountFrequency (%)
54.333333331
< 0.1%
511
< 0.1%
501
< 0.1%
481
< 0.1%
47.666666672
< 0.1%
46.51
< 0.1%
46.333333331
< 0.1%
462
< 0.1%
45.51
< 0.1%
45.251
< 0.1%

FiO2
Real number (ℝ)

MISSING
SKEWED

Distinct2106
Distinct (%)11.8%
Missing22527
Missing (%)55.8%
Infinite0
Infinite (%)0.0%
Mean0.5773836793
Minimum-16
Maximum1000.3
Zeros2
Zeros (%)< 0.1%
Negative2
Negative (%)< 0.1%
Memory size315.2 KiB
2021-11-29T11:25:40.015795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-16
5-th percentile0.28
Q10.4083333333
median0.5
Q30.6
95-th percentile0.875
Maximum1000.3
Range1016.3
Interquartile range (IQR)0.1916666667

Descriptive statistics

Standard deviation7.495152934
Coefficient of variation (CV)12.98123449
Kurtosis17776.81658
Mean0.5773836793
Median Absolute Deviation (MAD)0.1
Skewness133.2689459
Sum10282.62594
Variance56.1773175
MonotonicityNot monotonic
2021-11-29T11:25:40.118152image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.51650
 
4.1%
0.41636
 
4.1%
1638
 
1.6%
0.21592
 
1.5%
0.6541
 
1.3%
0.45436
 
1.1%
0.7348
 
0.9%
0.55276
 
0.7%
0.4243
 
0.6%
0.35239
 
0.6%
Other values (2096)11210
27.8%
(Missing)22527
55.8%
ValueCountFrequency (%)
-161
 
< 0.1%
-5.63751
 
< 0.1%
02
 
< 0.1%
0.022
 
< 0.1%
0.034
< 0.1%
0.045
< 0.1%
0.054
< 0.1%
0.064
< 0.1%
0.081
 
< 0.1%
0.111
 
< 0.1%
ValueCountFrequency (%)
1000.31
 
< 0.1%
101
 
< 0.1%
24
 
< 0.1%
1.61
 
< 0.1%
1.52
 
< 0.1%
1.2666666671
 
< 0.1%
1.2142857141
 
< 0.1%
1.21
 
< 0.1%
1.1666666672
 
< 0.1%
1638
1.6%

pH
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2349
Distinct (%)12.4%
Missing21401
Missing (%)53.1%
Infinite0
Infinite (%)0.0%
Mean7.382064509
Minimum6.63
Maximum7.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:40.223201image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.63
5-th percentile7.283333333
Q17.35
median7.384285714
Q37.42
95-th percentile7.475
Maximum7.73
Range1.1
Interquartile range (IQR)0.07

Descriptive statistics

Standard deviation0.06205049667
Coefficient of variation (CV)0.00840557497
Kurtosis6.819001289
Mean7.382064509
Median Absolute Deviation (MAD)0.03428571429
Skewness-1.089269525
Sum139779.3915
Variance0.003850264137
MonotonicityNot monotonic
2021-11-29T11:25:40.396222image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.38585
 
1.5%
7.4534
 
1.3%
7.37527
 
1.3%
7.42453
 
1.1%
7.41426
 
1.1%
7.43389
 
1.0%
7.36361
 
0.9%
7.35357
 
0.9%
7.39351
 
0.9%
7.34335
 
0.8%
Other values (2339)14617
36.2%
(Missing)21401
53.1%
ValueCountFrequency (%)
6.631
< 0.1%
6.651
< 0.1%
6.781
< 0.1%
6.811
< 0.1%
6.871
< 0.1%
6.91
< 0.1%
6.941
< 0.1%
6.941
< 0.1%
6.951
< 0.1%
6.961
< 0.1%
ValueCountFrequency (%)
7.731
 
< 0.1%
7.6951
 
< 0.1%
7.661
 
< 0.1%
7.631
 
< 0.1%
7.6151
 
< 0.1%
7.611
 
< 0.1%
7.64
< 0.1%
7.594
< 0.1%
7.5853
< 0.1%
7.5833333331
 
< 0.1%

PaCO2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2696
Distinct (%)14.7%
Missing21980
Missing (%)54.5%
Infinite0
Infinite (%)0.0%
Mean40.89645752
Minimum10
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:40.500386image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile30
Q136.25
median40
Q344
95-th percentile54.5
Maximum100
Range90
Interquartile range (IQR)7.75

Descriptive statistics

Standard deviation8.306837654
Coefficient of variation (CV)0.2031187579
Kurtosis6.927952056
Mean40.89645752
Median Absolute Deviation (MAD)4
Skewness1.761578454
Sum750695.3742
Variance69.00355181
MonotonicityNot monotonic
2021-11-29T11:25:40.594544image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
38456
 
1.1%
40453
 
1.1%
41417
 
1.0%
37403
 
1.0%
39402
 
1.0%
42395
 
1.0%
43365
 
0.9%
44357
 
0.9%
36357
 
0.9%
35333
 
0.8%
Other values (2686)14418
35.7%
(Missing)21980
54.5%
ValueCountFrequency (%)
101
 
< 0.1%
121
 
< 0.1%
153
< 0.1%
15.31
 
< 0.1%
15.52
< 0.1%
164
< 0.1%
16.71
 
< 0.1%
174
< 0.1%
184
< 0.1%
18.751
 
< 0.1%
ValueCountFrequency (%)
1001
< 0.1%
981
< 0.1%
96.751
< 0.1%
95.751
< 0.1%
95.333333331
< 0.1%
951
< 0.1%
94.666666671
< 0.1%
941
< 0.1%
93.51
< 0.1%
93.41
< 0.1%

SaO2
Real number (ℝ≥0)

MISSING

Distinct2279
Distinct (%)17.4%
Missing27248
Missing (%)67.6%
Infinite0
Infinite (%)0.0%
Mean93.6712575
Minimum29.5
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:40.692795image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum29.5
5-th percentile76.10875
Q193
median96.7
Q398
95-th percentile99.1
Maximum100
Range70.5
Interquartile range (IQR)5

Descriptive statistics

Standard deviation7.753211401
Coefficient of variation (CV)0.08277044216
Kurtosis8.309011815
Mean93.6712575
Median Absolute Deviation (MAD)1.7
Skewness-2.650466565
Sum1225969.418
Variance60.11228703
MonotonicityNot monotonic
2021-11-29T11:25:40.792664image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
981077
 
2.7%
97631
 
1.6%
99403
 
1.0%
96348
 
0.9%
97.5279
 
0.7%
98.5233
 
0.6%
95184
 
0.5%
96.5165
 
0.4%
94129
 
0.3%
95.5102
 
0.3%
Other values (2269)9537
 
23.6%
(Missing)27248
67.6%
ValueCountFrequency (%)
29.51
< 0.1%
301
< 0.1%
31.51
< 0.1%
32.251
< 0.1%
401
< 0.1%
41.251
< 0.1%
41.333333331
< 0.1%
41.51
< 0.1%
421
< 0.1%
431
< 0.1%
ValueCountFrequency (%)
10019
< 0.1%
99.930
0.1%
99.851
 
< 0.1%
99.838461541
 
< 0.1%
99.833333333
 
< 0.1%
99.82
 
< 0.1%
99.834
0.1%
99.7751
 
< 0.1%
99.753
 
< 0.1%
99.738888891
 
< 0.1%

AST
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct1928
Distinct (%)13.4%
Missing25979
Missing (%)64.4%
Infinite0
Infinite (%)0.0%
Mean136.7053508
Minimum3
Maximum9264
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:40.899109image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile13
Q120
median33
Q368
95-th percentile442
Maximum9264
Range9261
Interquartile range (IQR)48

Descriptive statistics

Standard deviation507.0128246
Coefficient of variation (CV)3.708800144
Kurtosis103.5586421
Mean136.7053508
Median Absolute Deviation (MAD)16
Skewness9.20935875
Sum1962678.721
Variance257062.0044
MonotonicityNot monotonic
2021-11-29T11:25:40.997237image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19388
 
1.0%
18388
 
1.0%
17373
 
0.9%
21348
 
0.9%
20347
 
0.9%
16344
 
0.9%
24333
 
0.8%
22332
 
0.8%
15317
 
0.8%
23292
 
0.7%
Other values (1918)10895
27.0%
(Missing)25979
64.4%
ValueCountFrequency (%)
32
 
< 0.1%
41
 
< 0.1%
53
 
< 0.1%
5.51
 
< 0.1%
610
 
< 0.1%
6.52
 
< 0.1%
712
< 0.1%
825
0.1%
8.252
 
< 0.1%
8.41
 
< 0.1%
ValueCountFrequency (%)
92641
< 0.1%
92101
< 0.1%
85911
< 0.1%
79061
< 0.1%
7868.81
< 0.1%
7697.3333331
< 0.1%
7438.51
< 0.1%
73931
< 0.1%
7279.41
< 0.1%
71741
< 0.1%

BUN
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct1888
Distinct (%)4.9%
Missing2018
Missing (%)5.0%
Infinite0
Infinite (%)0.0%
Mean22.02497686
Minimum1
Maximum227.3333333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:41.098571image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.5
Q111.5
median16.5
Q325.5
95-th percentile58.33333333
Maximum227.3333333
Range226.3333333
Interquartile range (IQR)14

Descriptive statistics

Standard deviation17.8934241
Coefficient of variation (CV)0.8124151145
Kurtosis10.25054004
Mean22.02497686
Median Absolute Deviation (MAD)6
Skewness2.688473175
Sum843953.0634
Variance320.174626
MonotonicityNot monotonic
2021-11-29T11:25:41.191772image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
131219
 
3.0%
121192
 
3.0%
141159
 
2.9%
111154
 
2.9%
101087
 
2.7%
151027
 
2.5%
16970
 
2.4%
9926
 
2.3%
17913
 
2.3%
18805
 
2.0%
Other values (1878)27866
69.1%
(Missing)2018
 
5.0%
ValueCountFrequency (%)
16
 
< 0.1%
1.251
 
< 0.1%
1.2857142861
 
< 0.1%
1.56
 
< 0.1%
1.5384615381
 
< 0.1%
1.5833333332
 
< 0.1%
1.6666666677
 
< 0.1%
1.751
 
< 0.1%
1.8571428571
 
< 0.1%
224
0.1%
ValueCountFrequency (%)
227.33333331
< 0.1%
192.83333331
< 0.1%
187.51
< 0.1%
181.61
< 0.1%
179.51
< 0.1%
178.51
< 0.1%
1781
< 0.1%
1771
< 0.1%
1721
< 0.1%
170.51
< 0.1%

Alkalinephos
Real number (ℝ≥0)

MISSING

Distinct1548
Distinct (%)10.9%
Missing26163
Missing (%)64.9%
Infinite0
Infinite (%)0.0%
Mean96.84900819
Minimum7
Maximum3726
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:41.288155image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile36
Q154
median72
Q3103
95-th percentile232.7
Maximum3726
Range3719
Interquartile range (IQR)49

Descriptive statistics

Standard deviation104.4976694
Coefficient of variation (CV)1.078975111
Kurtosis188.7363844
Mean96.84900819
Median Absolute Deviation (MAD)22
Skewness9.637277759
Sum1372640.993
Variance10919.76291
MonotonicityNot monotonic
2021-11-29T11:25:41.388319image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55182
 
0.5%
53178
 
0.4%
52175
 
0.4%
69173
 
0.4%
59173
 
0.4%
49169
 
0.4%
58168
 
0.4%
63167
 
0.4%
61166
 
0.4%
54166
 
0.4%
Other values (1538)12456
30.9%
(Missing)26163
64.9%
ValueCountFrequency (%)
71
 
< 0.1%
112
 
< 0.1%
121
 
< 0.1%
131
 
< 0.1%
141
 
< 0.1%
152
 
< 0.1%
162
 
< 0.1%
171
 
< 0.1%
185
< 0.1%
18.333333331
 
< 0.1%
ValueCountFrequency (%)
37261
< 0.1%
25281
< 0.1%
2182.6666671
< 0.1%
2145.51
< 0.1%
20201
< 0.1%
16691
< 0.1%
16502
< 0.1%
15291
< 0.1%
1477.6666671
< 0.1%
14371
< 0.1%

Calcium
Real number (ℝ≥0)

MISSING

Distinct4144
Distinct (%)11.8%
Missing5339
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean8.029117876
Minimum1.063333333
Maximum27.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:41.495324image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1.063333333
5-th percentile4.775
Q17.75
median8.3
Q38.75
95-th percentile9.4
Maximum27.45
Range26.38666667
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.404968293
Coefficient of variation (CV)0.1749841408
Kurtosis7.992568455
Mean8.029117876
Median Absolute Deviation (MAD)0.5
Skewness-0.9587080382
Sum280995.0383
Variance1.973935904
MonotonicityNot monotonic
2021-11-29T11:25:41.594951image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.51303
 
3.2%
8.31152
 
2.9%
8.61139
 
2.8%
8.41108
 
2.7%
8.21046
 
2.6%
8.1991
 
2.5%
8.7968
 
2.4%
8.8964
 
2.4%
8926
 
2.3%
9813
 
2.0%
Other values (4134)24587
61.0%
(Missing)5339
 
13.2%
ValueCountFrequency (%)
1.0633333331
 
< 0.1%
1.071
 
< 0.1%
1.083
< 0.1%
1.0851
 
< 0.1%
1.091
 
< 0.1%
1.12
< 0.1%
1.111
 
< 0.1%
1.121
 
< 0.1%
1.1251
 
< 0.1%
1.133
< 0.1%
ValueCountFrequency (%)
27.451
 
< 0.1%
25.21
 
< 0.1%
23.71
 
< 0.1%
19.11
 
< 0.1%
18.82
< 0.1%
18.63
< 0.1%
18.31
 
< 0.1%
18.23
< 0.1%
18.11
 
< 0.1%
182
< 0.1%

Chloride
Real number (ℝ≥0)

MISSING

Distinct1022
Distinct (%)4.8%
Missing18925
Missing (%)46.9%
Infinite0
Infinite (%)0.0%
Mean105.5508098
Minimum67.5
Maximum138.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:41.694543image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum67.5
5-th percentile97
Q1102.6666667
median106
Q3108.6666667
95-th percentile113.25
Maximum138.6
Range71.1
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.117964961
Coefficient of variation (CV)0.04848816386
Kurtosis1.91195008
Mean105.5508098
Median Absolute Deviation (MAD)3
Skewness-0.3040993965
Sum2259948.388
Variance26.19356534
MonotonicityNot monotonic
2021-11-29T11:25:41.867063image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1071013
 
2.5%
1061007
 
2.5%
105978
 
2.4%
108879
 
2.2%
103827
 
2.1%
104795
 
2.0%
109727
 
1.8%
102604
 
1.5%
110574
 
1.4%
101522
 
1.3%
Other values (1012)13485
33.4%
(Missing)18925
46.9%
ValueCountFrequency (%)
67.51
 
< 0.1%
731
 
< 0.1%
742
< 0.1%
75.555555561
 
< 0.1%
78.285714291
 
< 0.1%
79.666666671
 
< 0.1%
80.333333331
 
< 0.1%
813
< 0.1%
81.333333331
 
< 0.1%
822
< 0.1%
ValueCountFrequency (%)
138.61
< 0.1%
135.1251
< 0.1%
133.751
< 0.1%
1331
< 0.1%
132.83333331
< 0.1%
1321
< 0.1%
1312
< 0.1%
129.89473681
< 0.1%
1291
< 0.1%
128.52
< 0.1%

Creatinine
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4367
Distinct (%)11.4%
Missing2049
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean1.432323794
Minimum0.1
Maximum27.4
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:41.971450image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.5
Q10.7
median0.9
Q31.3
95-th percentile4.72675
Maximum27.4
Range27.3
Interquartile range (IQR)0.6

Descriptive statistics

Standard deviation1.774699753
Coefficient of variation (CV)1.239035307
Kurtosis30.01223009
Mean1.432323794
Median Absolute Deviation (MAD)0.25
Skewness4.707721647
Sum54839.38111
Variance3.149559212
MonotonicityNot monotonic
2021-11-29T11:25:42.067250image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.71444
 
3.6%
0.81424
 
3.5%
0.91318
 
3.3%
0.61235
 
3.1%
1987
 
2.4%
0.5777
 
1.9%
0.75713
 
1.8%
1.1594
 
1.5%
0.85454
 
1.1%
0.65436
 
1.1%
Other values (4357)28905
71.7%
(Missing)2049
 
5.1%
ValueCountFrequency (%)
0.13
 
< 0.1%
0.11
 
< 0.1%
0.13333333333
 
< 0.1%
0.153
 
< 0.1%
0.16666666671
 
< 0.1%
0.23
 
< 0.1%
0.211
< 0.1%
0.24
 
< 0.1%
0.222
 
< 0.1%
0.23333333332
 
< 0.1%
ValueCountFrequency (%)
27.41
< 0.1%
25.331
< 0.1%
251
< 0.1%
24.571
< 0.1%
23.831
< 0.1%
23.8251
< 0.1%
23.4951
< 0.1%
23.4851
< 0.1%
23.4351
< 0.1%
21.311
< 0.1%

Bilirubin_direct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct355
Distinct (%)17.3%
Missing38279
Missing (%)94.9%
Infinite0
Infinite (%)0.0%
Mean1.266791265
Minimum0.01
Maximum37.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:42.170581image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.1
Q10.1
median0.3
Q31
95-th percentile5.567333333
Maximum37.5
Range37.49
Interquartile range (IQR)0.9

Descriptive statistics

Standard deviation3.036609718
Coefficient of variation (CV)2.397087666
Kurtosis38.39248992
Mean1.266791265
Median Absolute Deviation (MAD)0.2
Skewness5.445914537
Sum2605.789633
Variance9.220998579
MonotonicityNot monotonic
2021-11-29T11:25:42.270598image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1468
 
1.2%
0.2314
 
0.8%
0.3147
 
0.4%
0.4118
 
0.3%
0.558
 
0.1%
0.651
 
0.1%
0.730
 
0.1%
0.829
 
0.1%
129
 
0.1%
1.124
 
0.1%
Other values (345)789
 
2.0%
(Missing)38279
94.9%
ValueCountFrequency (%)
0.015
< 0.1%
0.024
< 0.1%
0.035
< 0.1%
0.044
< 0.1%
0.051
 
< 0.1%
0.054
< 0.1%
0.066
< 0.1%
0.061
 
< 0.1%
0.077
< 0.1%
0.084
< 0.1%
ValueCountFrequency (%)
37.51
< 0.1%
351
< 0.1%
301
< 0.1%
25.951
< 0.1%
24.0351
< 0.1%
22.21
< 0.1%
21.3351
< 0.1%
21.22
< 0.1%
211
< 0.1%
20.571
< 0.1%

Glucose
Real number (ℝ≥0)

MISSING

Distinct9704
Distinct (%)25.0%
Missing1580
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean131.8109752
Minimum19
Maximum693.1333333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:42.375283image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum19
5-th percentile88.33333333
Q1108.0977273
median124.5857843
Q3145.2076923
95-th percentile202
Maximum693.1333333
Range674.1333333
Interquartile range (IQR)37.10996503

Descriptive statistics

Standard deviation37.82836884
Coefficient of variation (CV)0.2869895226
Kurtosis11.43664484
Mean131.8109752
Median Absolute Deviation (MAD)18.08578431
Skewness2.238849778
Sum5108466.154
Variance1430.985489
MonotonicityNot monotonic
2021-11-29T11:25:42.476368image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105205
 
0.5%
120199
 
0.5%
114195
 
0.5%
110194
 
0.5%
112193
 
0.5%
118193
 
0.5%
116192
 
0.5%
99191
 
0.5%
121191
 
0.5%
104185
 
0.5%
Other values (9694)36818
91.3%
(Missing)1580
 
3.9%
ValueCountFrequency (%)
191
< 0.1%
311
< 0.1%
382
< 0.1%
401
< 0.1%
411
< 0.1%
422
< 0.1%
441
< 0.1%
461
< 0.1%
472
< 0.1%
481
< 0.1%
ValueCountFrequency (%)
693.13333331
< 0.1%
671.51
< 0.1%
6661
< 0.1%
5631
< 0.1%
521.33333331
< 0.1%
509.251
< 0.1%
5011
< 0.1%
499.33333331
< 0.1%
4721
< 0.1%
4631
< 0.1%

Lactate
Real number (ℝ≥0)

MISSING

Distinct3010
Distinct (%)24.1%
Missing27843
Missing (%)69.0%
Infinite0
Infinite (%)0.0%
Mean2.16209565
Minimum0.3
Maximum26.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:42.582256image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.81
Q11.22
median1.7
Q32.46
95-th percentile4.975
Maximum26.95
Range26.65
Interquartile range (IQR)1.24

Descriptive statistics

Standard deviation1.750552825
Coefficient of variation (CV)0.8096555883
Kurtosis29.28618558
Mean2.16209565
Median Absolute Deviation (MAD)0.55
Skewness4.330777557
Sum27011.06095
Variance3.064435194
MonotonicityNot monotonic
2021-11-29T11:25:42.685546image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1324
 
0.8%
1.2324
 
0.8%
1.3312
 
0.8%
1.4285
 
0.7%
0.9273
 
0.7%
1.1272
 
0.7%
1.5256
 
0.6%
1.6233
 
0.6%
1.7202
 
0.5%
0.8201
 
0.5%
Other values (3000)9811
 
24.3%
(Missing)27843
69.0%
ValueCountFrequency (%)
0.32
 
< 0.1%
0.3251
 
< 0.1%
0.371
 
< 0.1%
0.44
 
< 0.1%
0.523
0.1%
0.541
 
< 0.1%
0.558
 
< 0.1%
0.562
 
< 0.1%
0.56666666672
 
< 0.1%
0.574
 
< 0.1%
ValueCountFrequency (%)
26.951
< 0.1%
25.051
< 0.1%
21.788888891
< 0.1%
21.043636361
< 0.1%
19.4251
< 0.1%
19.121
< 0.1%
191
< 0.1%
18.72
< 0.1%
18.6251
< 0.1%
17.81
< 0.1%

Magnesium
Real number (ℝ≥0)

MISSING

Distinct890
Distinct (%)2.5%
Missing4931
Missing (%)12.2%
Infinite0
Infinite (%)0.0%
Mean2.021546429
Minimum0.5
Maximum8.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:42.787270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile1.6
Q11.833333333
median2
Q32.166666667
95-th percentile2.516666667
Maximum8.2
Range7.7
Interquartile range (IQR)0.3333333333

Descriptive statistics

Standard deviation0.3180493465
Coefficient of variation (CV)0.1573297264
Kurtosis22.13330849
Mean2.021546429
Median Absolute Deviation (MAD)0.1666666667
Skewness2.187066243
Sum71572.85132
Variance0.1011553868
MonotonicityNot monotonic
2021-11-29T11:25:42.883436image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23210
 
8.0%
1.92659
 
6.6%
2.12508
 
6.2%
1.82207
 
5.5%
2.21645
 
4.1%
1.71494
 
3.7%
2.31100
 
2.7%
2.051004
 
2.5%
1.85905
 
2.2%
1.6893
 
2.2%
Other values (880)17780
44.1%
(Missing)4931
 
12.2%
ValueCountFrequency (%)
0.51
 
< 0.1%
0.651
 
< 0.1%
0.81
 
< 0.1%
0.94
 
< 0.1%
113
< 0.1%
1.053
 
< 0.1%
1.0666666671
 
< 0.1%
1.126
0.1%
1.153
 
< 0.1%
1.1666666671
 
< 0.1%
ValueCountFrequency (%)
8.21
< 0.1%
8.0428571431
< 0.1%
7.2666666671
< 0.1%
6.81
< 0.1%
6.6751
< 0.1%
6.51
< 0.1%
6.351
< 0.1%
6.22
< 0.1%
6.0333333331
< 0.1%
5.341
< 0.1%

Phosphate
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct1475
Distinct (%)5.2%
Missing12015
Missing (%)29.8%
Infinite0
Infinite (%)0.0%
Mean3.542320088
Minimum0.45
Maximum14.46666667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:42.986209image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.45
5-th percentile2.05
Q12.8
median3.35
Q34
95-th percentile5.8
Maximum14.46666667
Range14.01666667
Interquartile range (IQR)1.2

Descriptive statistics

Standard deviation1.213184876
Coefficient of variation (CV)0.3424831314
Kurtosis6.257406453
Mean3.542320088
Median Absolute Deviation (MAD)0.6166666667
Skewness1.76511785
Sum100322.0472
Variance1.471817544
MonotonicityNot monotonic
2021-11-29T11:25:43.086060image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.5793
 
2.0%
3786
 
1.9%
3.4748
 
1.9%
3.2748
 
1.9%
3.1740
 
1.8%
3.3738
 
1.8%
2.9676
 
1.7%
2.8657
 
1.6%
3.6641
 
1.6%
3.7626
 
1.6%
Other values (1465)21168
52.5%
(Missing)12015
29.8%
ValueCountFrequency (%)
0.451
 
< 0.1%
0.63
 
< 0.1%
0.651
 
< 0.1%
0.72
 
< 0.1%
0.89
< 0.1%
0.852
 
< 0.1%
0.881
 
< 0.1%
0.94
< 0.1%
0.91428571431
 
< 0.1%
0.952
 
< 0.1%
ValueCountFrequency (%)
14.466666671
 
< 0.1%
14.451
 
< 0.1%
13.3751
 
< 0.1%
13.31
 
< 0.1%
13.216666671
 
< 0.1%
131
 
< 0.1%
12.91
 
< 0.1%
12.41
 
< 0.1%
12.11
 
< 0.1%
126
< 0.1%

Potassium
Real number (ℝ≥0)

MISSING

Distinct2776
Distinct (%)7.2%
Missing1867
Missing (%)4.6%
Infinite0
Infinite (%)0.0%
Mean4.096041493
Minimum1.825
Maximum9.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:43.267456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1.825
5-th percentile3.4
Q13.8
median4.042857143
Q34.35
95-th percentile4.972071429
Maximum9.8
Range7.975
Interquartile range (IQR)0.55

Descriptive statistics

Standard deviation0.4948412672
Coefficient of variation (CV)0.1208096324
Kurtosis4.850219873
Mean4.096041493
Median Absolute Deviation (MAD)0.2761904762
Skewness1.125918109
Sum157570.6202
Variance0.2448678797
MonotonicityNot monotonic
2021-11-29T11:25:43.368610image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41805
 
4.5%
3.91580
 
3.9%
4.11381
 
3.4%
3.81323
 
3.3%
4.21176
 
2.9%
3.71086
 
2.7%
4.31007
 
2.5%
3.6930
 
2.3%
4.4786
 
1.9%
3.5749
 
1.9%
Other values (2766)26646
66.1%
(Missing)1867
 
4.6%
ValueCountFrequency (%)
1.8251
 
< 0.1%
2.21
 
< 0.1%
2.33
< 0.1%
2.3251
 
< 0.1%
2.41
 
< 0.1%
2.481
 
< 0.1%
2.53
< 0.1%
2.5333333331
 
< 0.1%
2.553
< 0.1%
2.5666666671
 
< 0.1%
ValueCountFrequency (%)
9.81
 
< 0.1%
9.42
< 0.1%
9.22
< 0.1%
91
 
< 0.1%
8.4751
 
< 0.1%
8.461
 
< 0.1%
8.21
 
< 0.1%
7.91
 
< 0.1%
7.81
 
< 0.1%
7.63
< 0.1%

Bilirubin_total
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct930
Distinct (%)6.5%
Missing26088
Missing (%)64.7%
Infinite0
Infinite (%)0.0%
Mean1.459475069
Minimum0.1
Maximum49.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:43.473047image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.3
Q10.5
median0.75
Q31.26
95-th percentile4.3
Maximum49.2
Range49.1
Interquartile range (IQR)0.76

Descriptive statistics

Standard deviation3.037348766
Coefficient of variation (CV)2.081124118
Kurtosis72.11863279
Mean1.459475069
Median Absolute Deviation (MAD)0.35
Skewness7.5132317
Sum20794.60079
Variance9.225487529
MonotonicityNot monotonic
2021-11-29T11:25:43.574920image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.51221
 
3.0%
0.41130
 
2.8%
0.61129
 
2.8%
0.71040
 
2.6%
0.3855
 
2.1%
0.8847
 
2.1%
0.9694
 
1.7%
1554
 
1.4%
0.2458
 
1.1%
1.1403
 
1.0%
Other values (920)5917
 
14.7%
(Missing)26088
64.7%
ValueCountFrequency (%)
0.189
 
0.2%
0.1251
 
< 0.1%
0.13333333335
 
< 0.1%
0.151
 
< 0.1%
0.1513
 
< 0.1%
0.16666666672
 
< 0.1%
0.22
 
< 0.1%
0.2458
1.1%
0.22
 
< 0.1%
0.221
 
< 0.1%
ValueCountFrequency (%)
49.21
< 0.1%
45.91
< 0.1%
45.751
< 0.1%
45.433333331
< 0.1%
44.966666671
< 0.1%
44.11
< 0.1%
43.21
< 0.1%
42.351
< 0.1%
41.61
< 0.1%
40.751
< 0.1%

TroponinI
Real number (ℝ≥0)

MISSING

Distinct2155
Distinct (%)30.6%
Missing33283
Missing (%)82.5%
Infinite0
Infinite (%)0.0%
Mean5.374386393
Minimum0.01
Maximum409.6833333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:43.677055image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.01
Q10.03
median0.1
Q31.255
95-th percentile32.168
Maximum409.6833333
Range409.6733333
Interquartile range (IQR)1.225

Descriptive statistics

Standard deviation18.68188074
Coefficient of variation (CV)3.476095572
Kurtosis78.41196216
Mean5.374386393
Median Absolute Deviation (MAD)0.09
Skewness7.270528377
Sum37905.54723
Variance349.0126681
MonotonicityNot monotonic
2021-11-29T11:25:43.772342image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.011209
 
3.0%
0.03775
 
1.9%
0.02275
 
0.7%
0.04237
 
0.6%
0.05135
 
0.3%
0.06113
 
0.3%
0.07113
 
0.3%
0.0878
 
0.2%
0.0974
 
0.2%
0.156
 
0.1%
Other values (2145)3988
 
9.9%
(Missing)33283
82.5%
ValueCountFrequency (%)
0.011209
3.0%
0.011428571431
 
< 0.1%
0.0124
 
< 0.1%
0.01251
 
< 0.1%
0.0133333333315
 
< 0.1%
0.0142
 
< 0.1%
0.01554
 
0.1%
0.016666666679
 
< 0.1%
0.017142857141
 
< 0.1%
0.01751
 
< 0.1%
ValueCountFrequency (%)
409.68333331
 
< 0.1%
298.831
 
< 0.1%
219.2851
 
< 0.1%
2005
< 0.1%
187.85333331
 
< 0.1%
187.85251
 
< 0.1%
183.51
 
< 0.1%
181.66333331
 
< 0.1%
180.081
 
< 0.1%
177.63251
 
< 0.1%

Hct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6029
Distinct (%)15.9%
Missing2317
Missing (%)5.7%
Infinite0
Infinite (%)0.0%
Mean32.04411709
Minimum9.3
Maximum68.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:43.870501image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum9.3
5-th percentile24.075
Q128.1
median31.45
Q335.6
95-th percentile41.7
Maximum68.04
Range58.74
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation5.43319845
Coefficient of variation (CV)0.1695536948
Kurtosis0.2852737323
Mean32.04411709
Median Absolute Deviation (MAD)3.661111111
Skewness0.482891185
Sum1218285.288
Variance29.5196454
MonotonicityNot monotonic
2021-11-29T11:25:43.967365image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
33.5154
 
0.4%
35141
 
0.3%
34138
 
0.3%
34.6128
 
0.3%
31.5128
 
0.3%
32.1127
 
0.3%
32.5127
 
0.3%
29.5127
 
0.3%
33.4127
 
0.3%
31126
 
0.3%
Other values (6019)36696
91.0%
(Missing)2317
 
5.7%
ValueCountFrequency (%)
9.31
< 0.1%
10.251
< 0.1%
11.861
< 0.1%
12.61
< 0.1%
13.31
< 0.1%
13.551
< 0.1%
14.61
< 0.1%
14.833333331
< 0.1%
15.51
< 0.1%
161
< 0.1%
ValueCountFrequency (%)
68.041
< 0.1%
651
< 0.1%
64.21
< 0.1%
64.11
< 0.1%
62.451
< 0.1%
61.71
< 0.1%
61.051
< 0.1%
59.851
< 0.1%
59.81
< 0.1%
58.151
< 0.1%

Hgb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct3027
Distinct (%)8.0%
Missing2448
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean10.71736803
Minimum2.6
Maximum26.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:44.068673image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.6
5-th percentile7.875
Q19.35
median10.55
Q311.93333333
95-th percentile14.1
Maximum26.6
Range24
Interquartile range (IQR)2.583333333

Descriptive statistics

Standard deviation1.897156337
Coefficient of variation (CV)0.1770170001
Kurtosis0.5869283979
Mean10.71736803
Median Absolute Deviation (MAD)1.261882353
Skewness0.5049037064
Sum406059.6398
Variance3.599202167
MonotonicityNot monotonic
2021-11-29T11:25:44.170271image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.5436
 
1.1%
10384
 
1.0%
10.6377
 
0.9%
11.3372
 
0.9%
11370
 
0.9%
9.5367
 
0.9%
10.9364
 
0.9%
11.2359
 
0.9%
9.9348
 
0.9%
10.8348
 
0.9%
Other values (3017)34163
84.7%
(Missing)2448
 
6.1%
ValueCountFrequency (%)
2.61
< 0.1%
3.3251
< 0.1%
41
< 0.1%
4.1751
< 0.1%
4.31
< 0.1%
4.51
< 0.1%
4.81
< 0.1%
4.91
< 0.1%
51
< 0.1%
5.11
< 0.1%
ValueCountFrequency (%)
26.61
< 0.1%
24.82
< 0.1%
23.81
< 0.1%
23.51
< 0.1%
22.51
< 0.1%
21.61
< 0.1%
21.21
< 0.1%
211
< 0.1%
20.961
< 0.1%
20.61
< 0.1%

PTT
Real number (ℝ≥0)

MISSING

Distinct4477
Distinct (%)22.1%
Missing20098
Missing (%)49.8%
Infinite0
Infinite (%)0.0%
Mean37.20801695
Minimum17.1
Maximum250
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:44.268531image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum17.1
5-th percentile23.25
Q127.3
median31.3
Q338.5
95-th percentile74.37166667
Maximum250
Range232.9
Interquartile range (IQR)11.2

Descriptive statistics

Standard deviation19.44373352
Coefficient of variation (CV)0.5225683901
Kurtosis25.1282612
Mean37.20801695
Median Absolute Deviation (MAD)4.9
Skewness3.998991833
Sum753015.8471
Variance378.0587731
MonotonicityNot monotonic
2021-11-29T11:25:44.367391image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28115
 
0.3%
28.6108
 
0.3%
29.5106
 
0.3%
28.9104
 
0.3%
27.6104
 
0.3%
28.1103
 
0.3%
26.5101
 
0.3%
29.3100
 
0.2%
27.7100
 
0.2%
28.799
 
0.2%
Other values (4467)19198
47.6%
(Missing)20098
49.8%
ValueCountFrequency (%)
17.11
< 0.1%
17.21
< 0.1%
17.31
< 0.1%
17.651
< 0.1%
18.11
< 0.1%
18.251
< 0.1%
18.42
< 0.1%
18.451
< 0.1%
18.52
< 0.1%
18.62
< 0.1%
ValueCountFrequency (%)
2503
 
< 0.1%
249.94
 
< 0.1%
24912
< 0.1%
237.51
 
< 0.1%
234.351
 
< 0.1%
212.71666671
 
< 0.1%
212.31
 
< 0.1%
2061
 
< 0.1%
204.91
 
< 0.1%
203.41251
 
< 0.1%

WBC
Real number (ℝ≥0)

MISSING

Distinct4042
Distinct (%)10.7%
Missing2625
Missing (%)6.5%
Infinite0
Infinite (%)0.0%
Mean11.07072318
Minimum0.1
Maximum328.3666667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:44.468482image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile4.666666667
Q17.6
median10.2
Q313.3
95-th percentile19.7
Maximum328.3666667
Range328.2666667
Interquartile range (IQR)5.7

Descriptive statistics

Standard deviation6.586209404
Coefficient of variation (CV)0.5949213339
Kurtosis380.6221748
Mean11.07072318
Median Absolute Deviation (MAD)2.8
Skewness12.12990773
Sum417488.042
Variance43.37815431
MonotonicityNot monotonic
2021-11-29T11:25:44.562321image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10220
 
0.5%
8.6216
 
0.5%
8215
 
0.5%
9.5210
 
0.5%
9.4210
 
0.5%
8.8208
 
0.5%
7.5208
 
0.5%
8.4206
 
0.5%
7.4206
 
0.5%
9.1205
 
0.5%
Other values (4032)35607
88.3%
(Missing)2625
 
6.5%
ValueCountFrequency (%)
0.110
< 0.1%
0.15
< 0.1%
0.151
 
< 0.1%
0.151
 
< 0.1%
0.16666666672
 
< 0.1%
0.210
< 0.1%
0.21
 
< 0.1%
0.23333333331
 
< 0.1%
0.251
 
< 0.1%
0.35
< 0.1%
ValueCountFrequency (%)
328.36666671
< 0.1%
305.751
< 0.1%
203.16666671
< 0.1%
200.81
< 0.1%
186.1251
< 0.1%
168.61
< 0.1%
168.121
< 0.1%
163.561
< 0.1%
152.91
< 0.1%
151.76666671
< 0.1%

Fibrinogen
Real number (ℝ≥0)

MISSING

Distinct1570
Distinct (%)34.8%
Missing35821
Missing (%)88.8%
Infinite0
Infinite (%)0.0%
Mean304.3572747
Minimum35
Maximum1383
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:44.737449image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile130
Q1197.5833333
median262
Q3368.5
95-th percentile634.3
Maximum1383
Range1348
Interquartile range (IQR)170.9166667

Descriptive statistics

Standard deviation157.4224107
Coefficient of variation (CV)0.5172290061
Kurtosis3.151959471
Mean304.3572747
Median Absolute Deviation (MAD)79
Skewness1.547339765
Sum1374173.095
Variance24781.8154
MonotonicityNot monotonic
2021-11-29T11:25:44.842384image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21730
 
0.1%
21423
 
0.1%
20321
 
0.1%
21520
 
< 0.1%
24819
 
< 0.1%
22318
 
< 0.1%
20818
 
< 0.1%
20218
 
< 0.1%
15117
 
< 0.1%
20017
 
< 0.1%
Other values (1560)4314
 
10.7%
(Missing)35821
88.8%
ValueCountFrequency (%)
351
< 0.1%
52.51
< 0.1%
55.51
< 0.1%
56.51
< 0.1%
581
< 0.1%
59.51
< 0.1%
611
< 0.1%
631
< 0.1%
641
< 0.1%
64.916666671
< 0.1%
ValueCountFrequency (%)
13831
 
< 0.1%
12461
 
< 0.1%
12111
 
< 0.1%
11611
 
< 0.1%
10301
 
< 0.1%
10007
< 0.1%
9761
 
< 0.1%
9601
 
< 0.1%
9561
 
< 0.1%
9541
 
< 0.1%

Platelets
Real number (ℝ≥0)

MISSING

Distinct4368
Distinct (%)11.6%
Missing2577
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean206.7748975
Minimum4
Maximum2322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:44.944517image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile82
Q1142
median191.25
Q3252
95-th percentile381
Maximum2322
Range2318
Interquartile range (IQR)110

Descriptive statistics

Standard deviation99.66729669
Coefficient of variation (CV)0.4820086861
Kurtosis13.87021048
Mean206.7748975
Median Absolute Deviation (MAD)54.25
Skewness2.040096468
Sum7807613.356
Variance9933.57003
MonotonicityNot monotonic
2021-11-29T11:25:45.040569image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
167135
 
0.3%
186132
 
0.3%
184131
 
0.3%
158130
 
0.3%
182127
 
0.3%
165126
 
0.3%
163125
 
0.3%
151122
 
0.3%
173122
 
0.3%
180121
 
0.3%
Other values (4358)36488
90.5%
(Missing)2577
 
6.4%
ValueCountFrequency (%)
42
< 0.1%
4.52
< 0.1%
53
< 0.1%
72
< 0.1%
81
 
< 0.1%
9.3333333331
 
< 0.1%
9.51
 
< 0.1%
9.7272727271
 
< 0.1%
101
 
< 0.1%
10.21
 
< 0.1%
ValueCountFrequency (%)
23221
< 0.1%
1687.51
< 0.1%
15441
< 0.1%
13431
< 0.1%
1300.51
< 0.1%
1187.751
< 0.1%
1113.751
< 0.1%
1101.3333331
< 0.1%
1096.51
< 0.1%
1067.51
< 0.1%

Age
Real number (ℝ≥0)

Distinct7296
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.64342324
Minimum14
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:45.139654image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile30
Q151
median63.11
Q374
95-th percentile85
Maximum100
Range86
Interquartile range (IQR)23

Descriptive statistics

Standard deviation16.48294561
Coefficient of variation (CV)0.2673917954
Kurtosis-0.2334728394
Mean61.64342324
Median Absolute Deviation (MAD)11.27
Skewness-0.4250999292
Sum2486449.12
Variance271.6874961
MonotonicityNot monotonic
2021-11-29T11:25:45.238390image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
67581
 
1.4%
68545
 
1.4%
66521
 
1.3%
65512
 
1.3%
61502
 
1.2%
69498
 
1.2%
71490
 
1.2%
62480
 
1.2%
70478
 
1.2%
63473
 
1.2%
Other values (7286)35256
87.4%
ValueCountFrequency (%)
142
 
< 0.1%
152
 
< 0.1%
165
 
< 0.1%
1713
< 0.1%
1832
0.1%
18.113
 
< 0.1%
18.131
 
< 0.1%
18.142
 
< 0.1%
18.151
 
< 0.1%
18.181
 
< 0.1%
ValueCountFrequency (%)
100392
1.0%
89112
 
0.3%
88.991
 
< 0.1%
88.982
 
< 0.1%
88.974
 
< 0.1%
88.961
 
< 0.1%
88.951
 
< 0.1%
88.953
 
< 0.1%
88.942
 
< 0.1%
88.931
 
< 0.1%

Gender
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size315.2 KiB
1.0
22566 
0.0
17770 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters121008
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row1.0

Common Values

ValueCountFrequency (%)
1.022566
55.9%
0.017770
44.1%

Length

2021-11-29T11:25:45.333622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:25:45.387855image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.022566
55.9%
0.017770
44.1%

Most occurring characters

ValueCountFrequency (%)
058106
48.0%
.40336
33.3%
122566
 
18.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number80672
66.7%
Other Punctuation40336
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
058106
72.0%
122566
 
28.0%
Other Punctuation
ValueCountFrequency (%)
.40336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common121008
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
058106
48.0%
.40336
33.3%
122566
 
18.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII121008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
058106
48.0%
.40336
33.3%
122566
 
18.6%

Unit1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing15617
Missing (%)38.7%
Memory size315.2 KiB
0.0
12452 
1.0
12267 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters74157
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row1.0
3rd row0.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
0.012452
30.9%
1.012267
30.4%
(Missing)15617
38.7%

Length

2021-11-29T11:25:45.441204image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:25:45.491452image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.012452
50.4%
1.012267
49.6%

Most occurring characters

ValueCountFrequency (%)
037171
50.1%
.24719
33.3%
112267
 
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number49438
66.7%
Other Punctuation24719
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
037171
75.2%
112267
 
24.8%
Other Punctuation
ValueCountFrequency (%)
.24719
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common74157
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
037171
50.1%
.24719
33.3%
112267
 
16.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII74157
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
037171
50.1%
.24719
33.3%
112267
 
16.5%

Unit2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing15617
Missing (%)38.7%
Memory size315.2 KiB
1.0
12452 
0.0
12267 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters74157
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row0.0
3rd row1.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
1.012452
30.9%
0.012267
30.4%
(Missing)15617
38.7%

Length

2021-11-29T11:25:45.545986image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:25:45.596270image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.012452
50.4%
0.012267
49.6%

Most occurring characters

ValueCountFrequency (%)
036986
49.9%
.24719
33.3%
112452
 
16.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number49438
66.7%
Other Punctuation24719
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
036986
74.8%
112452
 
25.2%
Other Punctuation
ValueCountFrequency (%)
.24719
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common74157
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
036986
49.9%
.24719
33.3%
112452
 
16.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII74157
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
036986
49.9%
.24719
33.3%
112452
 
16.8%

HospAdmTime
Real number (ℝ)

ZEROS

Distinct13626
Distinct (%)33.8%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-51.84894508
Minimum-5366.86
Maximum23.99
Zeros1313
Zeros (%)3.3%
Negative38767
Negative (%)96.1%
Memory size315.2 KiB
2021-11-29T11:25:45.658973image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-5366.86
5-th percentile-240.942
Q1-43.685
median-6.05
Q3-0.04
95-th percentile-0.01
Maximum23.99
Range5390.85
Interquartile range (IQR)43.645

Descriptive statistics

Standard deviation139.766452
Coefficient of variation (CV)-2.695646975
Kurtosis175.3735088
Mean-51.84894508
Median Absolute Deviation (MAD)6.03
Skewness-9.578944604
Sum-2091327.2
Variance19534.6611
MonotonicityNot monotonic
2021-11-29T11:25:45.764194image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.023799
 
9.4%
-0.031769
 
4.4%
01313
 
3.3%
-0.011235
 
3.1%
-0.04756
 
1.9%
-0.03365
 
0.9%
-0.05360
 
0.9%
-0.03353
 
0.9%
-0.07176
 
0.4%
-0.06169
 
0.4%
Other values (13616)30040
74.5%
ValueCountFrequency (%)
-5366.861
< 0.1%
-3710.661
< 0.1%
-3397.641
< 0.1%
-3342.341
< 0.1%
-3322.91
< 0.1%
-3269.11
< 0.1%
-3212.561
< 0.1%
-3189.391
< 0.1%
-3141.551
< 0.1%
-3112.121
< 0.1%
ValueCountFrequency (%)
23.991
< 0.1%
22.041
< 0.1%
20.041
< 0.1%
17.341
< 0.1%
16.021
< 0.1%
14.651
< 0.1%
14.211
< 0.1%
141
< 0.1%
11.941
< 0.1%
10.991
< 0.1%

ICULOS
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct276
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.26911444
Minimum4.5
Maximum320
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:45.867964image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum4.5
5-th percentile8
Q113
median20
Q324.5
95-th percentile30
Maximum320
Range315.5
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation11.69589542
Coefficient of variation (CV)0.57703041
Kurtosis64.42858314
Mean20.26911444
Median Absolute Deviation (MAD)5.5
Skewness5.556797402
Sum817575
Variance136.7939696
MonotonicityNot monotonic
2021-11-29T11:25:45.964691image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201273
 
3.2%
20.51248
 
3.1%
211241
 
3.1%
19.51233
 
3.1%
221227
 
3.0%
21.51220
 
3.0%
22.51149
 
2.8%
18.51148
 
2.8%
231120
 
2.8%
191113
 
2.8%
Other values (266)28364
70.3%
ValueCountFrequency (%)
4.5281
0.7%
5189
 
0.5%
5.5189
 
0.5%
6192
 
0.5%
6.5236
 
0.6%
7286
0.7%
7.5351
0.9%
8451
1.1%
8.5531
1.3%
9636
1.6%
ValueCountFrequency (%)
3201
 
< 0.1%
3091
 
< 0.1%
2861
 
< 0.1%
1701
 
< 0.1%
169.51
 
< 0.1%
1692
 
< 0.1%
168.510
< 0.1%
1681
 
< 0.1%
167.51
 
< 0.1%
165.51
 
< 0.1%

SepsisLabel
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct429
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02878767297
Minimum0
Maximum1
Zeros37404
Zeros (%)92.7%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:46.071136image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.1428571429
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.136403171
Coefficient of variation (CV)4.738249289
Kurtosis33.74885238
Mean0.02878767297
Median Absolute Deviation (MAD)0
Skewness5.704719793
Sum1161.179577
Variance0.01860582506
MonotonicityNot monotonic
2021-11-29T11:25:46.251992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
037404
92.7%
1426
 
1.1%
0.909090909156
 
0.1%
0.833333333352
 
0.1%
0.666666666746
 
0.1%
0.588235294139
 
0.1%
0.476190476239
 
0.1%
0.714285714337
 
0.1%
0.62536
 
0.1%
0.555555555636
 
0.1%
Other values (419)2165
 
5.4%
ValueCountFrequency (%)
037404
92.7%
0.0059880239521
 
< 0.1%
0.0063291139241
 
< 0.1%
0.011627906981
 
< 0.1%
0.013793103451
 
< 0.1%
0.017857142862
 
< 0.1%
0.02214022141
 
< 0.1%
0.022222222221
 
< 0.1%
0.026865671641
 
< 0.1%
0.027272727271
 
< 0.1%
ValueCountFrequency (%)
1426
1.1%
0.909090909156
 
0.1%
0.920
 
< 0.1%
0.833333333352
 
0.1%
0.818181818215
 
< 0.1%
0.769230769231
 
0.1%
0.7515
 
< 0.1%
0.714285714337
 
0.1%
0.692307692316
 
< 0.1%
0.666666666746
 
0.1%

Sepsis
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size315.2 KiB
0.0
37404 
1.0
 
2932

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters121008
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.037404
92.7%
1.02932
 
7.3%

Length

2021-11-29T11:25:46.348579image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T11:25:46.402860image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.037404
92.7%
1.02932
 
7.3%

Most occurring characters

ValueCountFrequency (%)
077740
64.2%
.40336
33.3%
12932
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number80672
66.7%
Other Punctuation40336
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
077740
96.4%
12932
 
3.6%
Other Punctuation
ValueCountFrequency (%)
.40336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common121008
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
077740
64.2%
.40336
33.3%
12932
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII121008
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
077740
64.2%
.40336
33.3%
12932
 
2.4%

Hours
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct273
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.48200119
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size315.2 KiB
2021-11-29T11:25:46.466930image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile14
Q124
median38
Q347
95-th percentile58
Maximum336
Range328
Interquartile range (IQR)23

Descriptive statistics

Standard deviation22.79592332
Coefficient of variation (CV)0.5923788425
Kurtosis42.42147962
Mean38.48200119
Median Absolute Deviation (MAD)11
Skewness4.840449261
Sum1552210
Variance519.6541201
MonotonicityNot monotonic
2021-11-29T11:25:46.567876image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
361364
 
3.4%
391362
 
3.4%
381323
 
3.3%
401285
 
3.2%
411271
 
3.2%
371223
 
3.0%
431210
 
3.0%
421193
 
3.0%
441143
 
2.8%
451089
 
2.7%
Other values (263)27873
69.1%
ValueCountFrequency (%)
8328
0.8%
9236
 
0.6%
10221
 
0.5%
11234
 
0.6%
12285
 
0.7%
13350
0.9%
14412
1.0%
15536
1.3%
16601
1.5%
17721
1.8%
ValueCountFrequency (%)
33610
< 0.1%
3353
 
< 0.1%
3342
 
< 0.1%
3331
 
< 0.1%
3301
 
< 0.1%
3281
 
< 0.1%
3271
 
< 0.1%
3261
 
< 0.1%
3201
 
< 0.1%
3181
 
< 0.1%

Interactions

2021-11-29T11:25:34.249864image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:26.718916image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:26.925199image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:27.122999image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:27.321703image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:27.582208image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:27.775573image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:27.967793image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.160182image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.343714image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.521332image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.702988image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.883533image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:29.067534image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:29.251737image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:29.430784image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:29.697333image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:29.881786image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:30.062557image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:30.263132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:30.448800image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:30.646533image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:30.832903image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:31.029751image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:31.227174image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:31.411274image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:31.604280image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:31.790996image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.049167image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.223212image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.394970image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.576804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.746809image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.918005image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.096241image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.281938image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.458174image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.630662image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.814396image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:34.068241image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:34.341625image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:26.821180image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:27.022132image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:27.220647image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:27.488471image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:27.677033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:27.870111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.061596image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.252181image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.430126image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.609529image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.791876image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:28.973399image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:29.157758image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:29.339536image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:29.524197image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:29.786785image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:29.971974image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:30.160084image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:30.354901image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:30.544897image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:30.739998image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:30.927639image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:31.128146image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:31.316081image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:31.506409image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:31.697272image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:31.956414image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.134679image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.305864image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.484108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.661053image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:32.829992image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.007516image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.185487image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.368020image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.542691image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.720577image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:33.903965image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T11:25:34.157043image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2021-11-29T11:25:46.717402image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-11-29T11:25:47.061468image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-11-29T11:25:47.407308image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-11-29T11:25:47.693009image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-11-29T11:25:34.593261image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2021-11-29T11:25:35.723182image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-11-29T11:25:36.611459image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-11-29T11:25:37.469575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

PatientIDHRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
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Last rows

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